Adaptive Observer-based Fast Fault Estimation

  • Zhang, Ke (College of Automation Engineering, Nanjing University of Aeronautics and Astronautics) ;
  • Jiang, Bin (College of Automation Engineering, Nanjing University of Aeronautics and Astronautics) ;
  • Cocquempot, Vincent (University of Sciences and Technologies of Lille Villeneuve d'Ascq Cedex)
  • 발행 : 2008.06.30

초록

This paper studies the problem of fault estimation using adaptive fault diagnosis observer. A fast adaptive fault estimation (FAFE) approximator is proposed to improve the rapidity of fault estimation. Then based on linear matrix inequality (LMI) technique, a feasible algorithm is explored to solve the designed parameters. Furthermore, an extension to sensor fault case is investigated. Finally, simulation results are presented to illustrate the efficiency of the proposed FAFE methodology.

키워드

참고문헌

  1. M. Basseville and I. V. Nikiforov, Detection of Abrupt Changes: Theory and Application, Prentice-Hall, Englewood Cliffs, NJ, 1993
  2. J. Chen and J. J. Patton, Robust Model-based Fault Diagnosis for Dynamic Systems, Kluwer Academic Publishers, Boston, MA, 1999
  3. M. Blanke, M. Kinnaert, J. Lunze, and M. Staroswiecki, Diagnosis and Fault-Tolerant Control, 2nd edition, Springer Verlag, Berlin Heidelberg, 2006
  4. J. J. Gertler, "Survey of model-based failure detection and isolation in complex plants," IEEE Control Systems Magazine, vol. 8, no.6, pp. 3-11, December 1988
  5. D. M. Frank, S. X. Ding, and B. Koppen-Seliger, "Current developments in the theory of FDI," Proc. of IFAC Safeprocess, pp. 16-27, 2000
  6. M. Kinnaert, "Fault diagnosis based on analytical models for linear and nonlinear systems - A tutorial," Proc. of IFAC Safeprocess, pp. 37-50, 2003
  7. M. M. Polycarpou, "Fault accommodation of a class of multivariable nonlinear dynamical systems using a learning approach," IEEE Trans. on Automatic Control, vol. 46, no. 5, pp. 736-742, May 2001 https://doi.org/10.1109/9.920792
  8. B. Jiang, M. Staroswiecki and V. Cocquempot, "Fault accommodation for nonlinear dynamic systems," IEEE Trans. on Automatic Control, vol. 51, no. 9, pp. 1578-1583, September 2006 https://doi.org/10.1109/TAC.2006.878732
  9. M. Staroswiecki, H. Yang, and B. Jiang, "Progressive accommodation of parametric faults in linear quadratic control," Automatica, vol. 43, no. 12, pp. 2070-2076, December 2007 https://doi.org/10.1016/j.automatica.2007.04.016
  10. H. Wang and S. Daley, "Actuator fault diagnosis: An adaptive observer-based technique," IEEE Trans. on Automatic Control, vol. 41, no. 7, pp. 1073-1078, July 1996 https://doi.org/10.1109/9.508919
  11. B. Jiang, J. L. Wang, and Y. C. Soh, "An adaptive technique for robust diagnosis of faults with independent effects on system outputs," International Journal of Control, vol. 75, no. 11, pp. 792-802, November 2002 https://doi.org/10.1080/00207170210149934
  12. A. Xu and Q. Zhang, "Residual generation for fault diagnosis in linear time-varying systems," IEEE Trans. on Automatic Control, vol. 49, no. 5, pp. 767-772, May 2004 https://doi.org/10.1109/TAC.2004.825983
  13. D. Berdjag, C. Christophe, V. Cocquempot, and B. Jiang, "Nonlinear model decomposition for robust fault detection and isolation using algebraic tools," International Journal of Innovative Computing, Information and Control, vol. 2, no. 6, pp. 1337-1354, December 2006
  14. A. Fekih, H. Xu, and F. N. Chowdhury, "Neural networks based system identification techniques for model based fault detection of nonlinear systems," International Journal of Innovative Computing, Information and Control, vol. 3, no. 5, pp. 1073-1085, October 2007
  15. B. Walcott and S. H. Zak, "Combined observercontroller synthesis for uncertain dynamic systems with applications," IEEE Trans. on Systems, Man and Cybernetics, vol. 18, no. 1, pp. 88-104, January/February 1988 https://doi.org/10.1109/21.87057
  16. M. Corless and J. Tu, "State and input estimation for a class of uncertain systems," Automatica, vol. 34, no.6, pp. 757-764, June 1998 https://doi.org/10.1016/S0005-1098(98)00013-2
  17. C. Edwards, "A comparison of sliding mode and unknown input observers for fault reconstruction," Proc. of the 43rd IEEE Conference on Decision and Control, pp. 5279- 5284, 2004
  18. T. G. Park and K. S. Lee, "Process fault isolation for linear systems with unknown inputs," IEE Proc. Control Theory Appl., vol. 151, no. 6, pp. 720-726, November 2004 https://doi.org/10.1049/ip-cta:20040796